Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …
potential for many fields—including medicine—to benefit from the insights that AI techniques …
Lack of transparency and potential bias in artificial intelligence data sets and algorithms: a scoping review
R Daneshjou, MP Smith, MD Sun… - JAMA …, 2021 - jamanetwork.com
Importance Clinical artificial intelligence (AI) algorithms have the potential to improve clinical
care, but fair, generalizable algorithms depend on the clinical data on which they are trained …
care, but fair, generalizable algorithms depend on the clinical data on which they are trained …
[HTML][HTML] Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts
Background Multiple studies have compared the performance of artificial intelligence (AI)–
based models for automated skin cancer classification to human experts, thus setting the …
based models for automated skin cancer classification to human experts, thus setting the …
Key challenges for delivering clinical impact with artificial intelligence
Background Artificial intelligence (AI) research in healthcare is accelerating rapidly, with
potential applications being demonstrated across various domains of medicine. However …
potential applications being demonstrated across various domains of medicine. However …
Designing deep learning studies in cancer diagnostics
A Kleppe, OJ Skrede, S De Raedt, K Liestøl… - Nature Reviews …, 2021 - nature.com
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
[HTML][HTML] Analysis of the ISIC image datasets: Usage, benchmarks and recommendations
Abstract The International Skin Imaging Collaboration (ISIC) datasets have become a
leading repository for researchers in machine learning for medical image analysis …
leading repository for researchers in machine learning for medical image analysis …
A deep learning system for differential diagnosis of skin diseases
Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most
cases are seen instead by general practitioners with lower diagnostic accuracy. We present …
cases are seen instead by general practitioners with lower diagnostic accuracy. We present …
Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in developing computer-aided diagnosis …
researchers have shown an increasing interest in developing computer-aided diagnosis …
Deep learning techniques for skin lesion analysis and melanoma cancer detection: a survey of state-of-the-art
Abstract Analysis of skin lesion images via visual inspection and manual examination to
diagnose skin cancer has always been cumbersome. This manual examination of skin …
diagnose skin cancer has always been cumbersome. This manual examination of skin …
A survey on deep learning applied to medical images: from simple artificial neural networks to generative models
P Celard, EL Iglesias, JM Sorribes-Fdez… - Neural Computing and …, 2023 - Springer
Deep learning techniques, in particular generative models, have taken on great importance
in medical image analysis. This paper surveys fundamental deep learning concepts related …
in medical image analysis. This paper surveys fundamental deep learning concepts related …